Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 129B, 1018WS, Amsterdam, The Netherlands.
Department of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
Neuropsychol Rev. 2020 Mar;30(1):51-96. doi: 10.1007/s11065-019-09423-6. Epub 2020 Feb 1.
Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.
许多神经心理学家认为,众多认知测试可以分为少数几个认知领域。然而,对于存在多少个领域、这些领域是什么以及哪些认知测试属于哪个领域,并没有达成共识。通过因素分析可以解决这种不确定性,前提是分析包括广泛的认知测试,这些测试已经在大量人群中进行了测试。在本文中,进行了两次这样的因素分析,每次都结合了多项研究。然而,由于不可能获得该领域中超过最常见测试变量的完整多元数据,因此并非所有可能的领域都在这里进行了检查。第一次分析是对 52 项研究中 60398 名健康参与者的相关矩阵进行的因子元分析。拟合了文献中的几种模型,其中基于 Cattell-Horn-Carroll (CHC) 模型的版本比其他模型更好地描述了相关性。第二次分析是对未包含在第一次元分析中的 54 项荷兰和比利时研究的 11881 名参与者的高级神经心理诊断基础设施 (ANDI) 数据库进行的因子分析。同样,CHC 模型的模型拟合度优于其他模型。因此,我们得出结论,CHC 模型最好地描述了认知领域以及哪些测试属于每个领域。因此,尽管最初是在智力文献中开发的,但 CHC 模型在神经心理学中值得更多关注。